# ScalarOp#

class qiskit.quantum_info.ScalarOp(dims=None, coeff=1)[source]#

Bases: LinearOp

Scalar identity operator class.

This is a symbolic representation of an scalar identity operator on multiple subsystems. It may be used to initialize a symbolic scalar multiplication of an identity and then be implicitly converted to other kinds of operator subclasses by using the compose(), dot(), tensor(), expand() methods.

Initialize an operator object.

Parameters:
• dims (int or tuple) – subsystem dimensions.

• coeff (Number) – scalar coefficient for the identity operator (Default: 1).

Raises:

QiskitError – If the optional coefficient is invalid.

Attributes

atol = 1e-08#
coeff#

Return the coefficient

dim#

Return tuple (input_shape, output_shape).

num_qubits#

Return the number of qubits if a N-qubit operator or None otherwise.

qargs#

Return the qargs for the operator.

rtol = 1e-05#

Methods

Return the adjoint of the Operator.

Return type:

Self

compose(other, qargs=None, front=False)[source]#

Return the operator composition with another ScalarOp.

Parameters:
• other (ScalarOp) – a ScalarOp object.

• qargs (list or None) – Optional, a list of subsystem positions to apply other on. If None apply on all subsystems (default: None).

• front (bool) – If True compose using right operator multiplication, instead of left multiplication [default: False].

Returns:

The composed ScalarOp.

Return type:

ScalarOp

Raises:

QiskitError – if other cannot be converted to an operator, or has incompatible dimensions for specified subsystems.

Note

Composition (&) by default is defined as left matrix multiplication for matrix operators, while @ (equivalent to dot()) is defined as right matrix multiplication. That is that A & B == A.compose(B) is equivalent to B @ A == B.dot(A) when A and B are of the same type.

Setting the front=True kwarg changes this to right matrix multiplication and is equivalent to the dot() method A.dot(B) == A.compose(B, front=True).

conjugate()[source]#

Return the conjugate of the ScalarOp.

copy()#

Make a deep copy of current operator.

dot(other, qargs=None)#

Return the right multiplied operator self * other.

Parameters:
• other (Operator) – an operator object.

• qargs (list or None) – Optional, a list of subsystem positions to apply other on. If None apply on all subsystems (default: None).

Returns:

The right matrix multiplied Operator.

Return type:

Operator

Note

The dot product can be obtained using the @ binary operator. Hence a.dot(b) is equivalent to a @ b.

expand(other)[source]#

Return the reverse-order tensor product with another ScalarOp.

Parameters:

other (ScalarOp) – a ScalarOp object.

Returns:

the tensor product $$b \otimes a$$, where $$a$$

is the current ScalarOp, and $$b$$ is the other ScalarOp.

Return type:

ScalarOp

input_dims(qargs=None)#

Return tuple of input dimension for specified subsystems.

is_unitary(atol=None, rtol=None)[source]#

Return True if operator is a unitary matrix.

output_dims(qargs=None)#

Return tuple of output dimension for specified subsystems.

power(n)[source]#

Return the power of the ScalarOp.

Parameters:

n (float) – the exponent for the scalar op.

Returns:

the coeff ** n ScalarOp.

Return type:

ScalarOp

reshape(input_dims=None, output_dims=None, num_qubits=None)#

Return a shallow copy with reshaped input and output subsystem dimensions.

Parameters:
• input_dims (None or tuple) – new subsystem input dimensions. If None the original input dims will be preserved [Default: None].

• output_dims (None or tuple) – new subsystem output dimensions. If None the original output dims will be preserved [Default: None].

• num_qubits (None or int) – reshape to an N-qubit operator [Default: None].

Returns:

returns self with reshaped input and output dimensions.

Return type:

BaseOperator

Raises:

QiskitError – if combined size of all subsystem input dimension or subsystem output dimensions is not constant.

tensor(other)[source]#

Return the tensor product with another ScalarOp.

Parameters:

other (ScalarOp) – a ScalarOp object.

Returns:

the tensor product $$a \otimes b$$, where $$a$$

is the current ScalarOp, and $$b$$ is the other ScalarOp.

Return type:

ScalarOp

Note

The tensor product can be obtained using the ^ binary operator. Hence a.tensor(b) is equivalent to a ^ b.

to_matrix()[source]#

Convert to a Numpy matrix.

to_operator()[source]#

Convert to an Operator object.

Return type:

Operator

transpose()[source]#

Return the transpose of the ScalarOp.